针对传统的相控阵雷达及多输入多输出(MIMO)雷达在面对与目标角度相同、距离不同的主瓣转发式干扰时无法有效地区分目标与假目标的问题,以及多类型主瓣干扰同时存在的抗干扰难题,基于频率分集阵列(FDA)-MIMO 雷达,提出了一种基于矩阵联合近似对角化(JADE)盲源分离算法的智能抗干扰方法。首先对接收信号进行波束形成处理,然后将波束输出信号进行匹配滤波处理。根据频率分集子频率受干扰的情况,自适应地选择干扰较弱的子频率,采用JADE 算法将干扰与目标分离开来,实现智能抗干扰。为了加强对主瓣瞄频及切片等转发干扰的对抗效果,针对每个频率分集子频率,采用低通窄带滤波,滤除干扰。仿真实验表明:将基于智能子频选取策略的接收波束域JADE 算法应用到FDA-MIMO雷达可以实现良好的抗主瓣干扰效果。

In view of the problem that the conventional phased array radar and multiple-input multiple-output (MIMO) radar cannot effectively distinguish between target and false target when facing the same angle and different distance from the main lobe distance forwarding jamming, an intelligent anti-jamming method based on matrix joint approximate diagonalization of eigenmatrixe (JADE) blind source separation algorithm is proposed based on frequency diversity array (FDA)-MIMO radar. This method is also effective for multi mainlobe jamming scenarios. The received signal is first beamformed, and then the beam output signal is matched filtered. According to the interference of the frequency diversity sub-frequency, the undisturbed sub-frequency is adaptively selected, and the JADE algorithm is used to separate the interference from the target, so as to realize intelligent anti-interference. In order to strengthen the countermeasure effect against false target forwarding interference, low-pass narrowband filtering is used for each frequency diversity sub-frequency to filter out-of-band interference. Simulation results show that the receiving beam domain JADE algorithm based on intelligent frequency selection strategy is applied to FDA-MIMO radar to achieve good mainlobe anti-jamming effect.

TN974